Benchmarking Object Detection Algorithms for Optical Character Recognition of Odometer Mileage

Machine learning algorithms have had breakthroughs in many areas in the last decades. The hardest task, to solve with machine learning, was solving tasks that humans solve intuitively, e.g. understanding natural language or recognizing specific objects in images. To overcome these problems is to allow the computer to learn from experience, instead of implementing a pre-written program to solve the problem at hand - that is how Neural Networks came to be. Neural Network is widely used in image analysis, and object detection algorithms have evolved considerably in the last years. Two of these algorithms are Faster Region-basedConvolutional Neural Networks(Faster R-CNN) and You Only Look Once(YOLO). The purpose of this thesis is to evaluate and benchmark state-of-the-art object detection methods and then analyze their performance based on reading information from images. The information that we aim to extract is digital and analog digits from the odometer of a car, this will be done through object recognition and region-based image analysis. Our models will be compared to the open-source Optical Character Recognition(OCR) model Tesseract, which is in production by the Stockholm-based company Greater Than. In this project we will take a more modern approach and focus on two object detection models, Faster R-CNN and YOLO. When training these models, we will use transfer learning. This means that we will use models that are pre-trained, in our case on a dataset called ImageNet, specifically for object detection. We will then use the TRODO dataset to train these models further, this dataset consists of 2 389 images of car odometers. The models are then evaluated through the measures of mean average precision(mAP), prediction accuracy, and Levenshtein Distance. Our findings are that the object detection models are out-performing Tesseract for all measurements. The highest mAP and accuracy is attained by Faster R-CNN while the best results, regarding Levenshtein distance, are achieved by a YOLO model. The final result is clear, both of our approaches have more diversity and are far better thanTesseract, for solving this specific problem

Benchmarking Object Detection Algorithms for Optical Character Recognition of Odometer Mileage

Machine learning algorithms have had breakthroughs in many areas in the last decades. The hardest task, to solve with machine learning, was solving tasks that humans solve intuitively, e.g. understanding natural language or recognizing specific objects in images. To overcome these problems is to allow the computer to learn from experience, instead of implementing a pre-written program to solve the problem at hand - that is how Neural Networks came to be. Neural Network is widely used in image analysis, and object detection algorithms have evolved considerably in the last years. Two of these algorithms are Faster Region-basedConvolutional Neural Networks(Faster R-CNN) and You Only Look Once(YOLO). The purpose of this thesis is to evaluate and benchmark state-of-the-art object detection methods and then analyze their performance based on reading information from images. The information that we aim to extract is digital and analog digits from the odometer of a car, this will be done through object recognition and region-based image analysis. Our models will be compared to the open-source Optical Character Recognition(OCR) model Tesseract, which is in production by the Stockholm-based company Greater Than. In this project we will take a more modern approach and focus on two object detection models, Faster R-CNN and YOLO. When training these models, we will use transfer learning. This means that we will use models that are pre-trained, in our case on a dataset called ImageNet, specifically for object detection. We will then use the TRODO dataset to train these models further, this dataset consists of 2 389 images of car odometers. The models are then evaluated through the measures of mean average precision(mAP), prediction accuracy, and Levenshtein Distance. Our findings are that the object detection models are out-performing Tesseract for all measurements. The highest mAP and accuracy is attained by Faster R-CNN while the best results, regarding Levenshtein distance, are achieved by a YOLO model. The final result is clear, both of our approaches have more diversity and are far better thanTesseract, for solving this specific problem

Upplevelser av teamarbete och dess effekter på patientsäkerheten inom ambulanssjukvården. : En kvalitativ intervjustudie

Introduction: The ambulance service has undergone significant changes, from a transport service to treating advanced and life-threatening conditions. This places great demands on the ambulance team responsible for patient care, and the specialist-trained ambulance nurse has a responsibility for ensuring effective teamwork. Previous research has shown that teamwork is strongly related to patient safety, but there is limited research on the ambulance nurses' own experiences of teamwork and how they perceive that teamwork affects patient safety. Aim: The aim of the study was to investigate ambulance nurses' experiences of collaboration in teams and their experiences of how teamwork affects patient safety. Method: Qualitative interview study with an inductive approach was used. Ten interviews were conducted with practicing ambulance nurses. The interviews were transcribed and analyzed according to Graneheim and Lundman's method for qualitative content analysis. Results: The results showed that there were factors that influenced how ambulance nurses experienced collaboration in the team, such as situational awareness, communication, competence and experience were identified. Shortcomings in one or more of these factors negatively affected the team and patient care. The team was positively affected when roles in the team were clear, and communication worked well. When team members had the same level of education, safety increased because they had similar pre-understanding and similar ways to care for the patients. Conclusion: This study has shown that patient care is affected by how teamwork works. The study can, therefore, be used for improving teamwork, which in turn would improve patient safety.Introduktion: Ambulanssjukvården har genomgått stora förändringar. Från att historiskt fungera som en ren transporttjänst till att idag behandla avancerade och livshotande tillstånd. Detta ställer stora krav på ambulansteamet som ansvarar för vården, och den specialistutbildade ambulanssjuksköterskan har ett särskilt ansvar för att teamarbetet fungerar. Tidigare forskning visar att teamarbetet står i stark relation till patientsäkerheten. Det finns dock begränsad forskning på ambulanssjuksköterskans egna erfarenheter av teamarbete och hur de upplever att teamarbetet påverkar patientsäkerheten. Syfte: Syftet med studien var att undersöka ambulanssjuksköterskors upplevelser av samverkan i team och deras erfarenheter av hur teamarbete påverkar patientsäkerheten. Metod: En kvalitativ intervjustudie med induktiv ansats användes. Tio intervjuer med yrkesverksamma ambulanssjuksköterskor genomfördes. Intervjuerna transkriberades för att sedan analyseras enligt Graneheim och Lundmans metod för kvalitativ innehållsanalys. Resultat: Resultatet visade att det fanns faktorer som påverkade hur ambulanssjuksköterskorna upplevde samverkan i teamet. Faktorer som situationsmedvetenhet, kommunikation, kompetens och erfarenhet identifierades. Fanns brister i någon eller flera av de faktorerna påverkades teamet negativt vilket även påverkade patientens omhändertagande negativt. Bland annat tog omhändertagandet längre tid och livsviktig behandling sattes inte in i rätt tid. Teamet påverkades positivt när rollerna i teamet var tydliga och kommunikationen fungerade. När teammedlemmarna hade samma utbildningsnivå ökade tryggheten då de hade liknande förförståelse och liknande sätt att se, bedöma och behandla patienten. Slutsats: Denna studie har visat att patientens omhändertagande påverkas av hur teamarbetet fungerar. Studien kan därför användas som grund för att förbättra teamarbetet inom ambulansen vilket i sin tur skulle förbättra patientsäkerheten

Småföretags Kommunikationskanaler : till externa resurser

Livskraftiga företag har en förmåga att använda sig av externa resurser för att kunna lösa sina problem där de interna resurserna inte är tillräckliga. Småföretag har inte möjlighet att ha alla resurser själva utan måste specialisera sig för att kunna bli mer konkurrenskraftiga i en ständigt ändrande omvärld. Syftet med denna undersökning är belysa vilka olika kommunikationskanaler småföretag använder sig av och vilka faktorer som påverkar valet när de söker externa resurser. Det teoretiska ramverket består av kommunikationsprocessen och kommunikationskanaler. Kommunikationskanalerna består av nätverk, internet, mässor och reklam.  Denna kvalitativa studie är utförd på småföretag inom metallbearbetningsindustrin. Insamling av data har genomförts med öppna individuella intervjuer med fem respondenter på utvalda företag. Resultatet består av respondenternas åsikter om kommunikationskanalerna och hur de använder dem. Nätverket har visat sig vara den mest förekommande kommunikationskanalen följt av sökmotorer och förmedlingstjänster. Dessa kanaler kan bistås med mässor och reklam vid sökandet av externa resurser. Viable companies have the ability to use external resources to help solve its problems when internal resources are not adequate. Small businesses do not have the option to have all of the resources in-house; they must specialize in order to become more competitive in a constantly changing environment. The purpose of this survey is to show the various communication channels, small businesses use and the factors that affect the choice of communication channel when seeking external resources. The theoretical framework is composed of the communication process and communication channels. The communication channel consists of networks, the internet, trade shows and advertising.  This qualitative study is carried out at small enterprises within the metal working industry. Data collection was carried out with open individual interviews with five respondents at selected companies. The result consists of the respondents ' views on the channels of communication and how they use them. The network has proven to be the most used communication channel followed by search engines and marketplaces. These channels can be assisted with trade shows and advertising in search of external resources

Upplevelser av teamarbete och dess effekter på patientsäkerheten inom ambulanssjukvården. : En kvalitativ intervjustudie

Introduction: The ambulance service has undergone significant changes, from a transport service to treating advanced and life-threatening conditions. This places great demands on the ambulance team responsible for patient care, and the specialist-trained ambulance nurse has a responsibility for ensuring effective teamwork. Previous research has shown that teamwork is strongly related to patient safety, but there is limited research on the ambulance nurses' own experiences of teamwork and how they perceive that teamwork affects patient safety. Aim: The aim of the study was to investigate ambulance nurses' experiences of collaboration in teams and their experiences of how teamwork affects patient safety. Method: Qualitative interview study with an inductive approach was used. Ten interviews were conducted with practicing ambulance nurses. The interviews were transcribed and analyzed according to Graneheim and Lundman's method for qualitative content analysis. Results: The results showed that there were factors that influenced how ambulance nurses experienced collaboration in the team, such as situational awareness, communication, competence and experience were identified. Shortcomings in one or more of these factors negatively affected the team and patient care. The team was positively affected when roles in the team were clear, and communication worked well. When team members had the same level of education, safety increased because they had similar pre-understanding and similar ways to care for the patients. Conclusion: This study has shown that patient care is affected by how teamwork works. The study can, therefore, be used for improving teamwork, which in turn would improve patient safety.Introduktion: Ambulanssjukvården har genomgått stora förändringar. Från att historiskt fungera som en ren transporttjänst till att idag behandla avancerade och livshotande tillstånd. Detta ställer stora krav på ambulansteamet som ansvarar för vården, och den specialistutbildade ambulanssjuksköterskan har ett särskilt ansvar för att teamarbetet fungerar. Tidigare forskning visar att teamarbetet står i stark relation till patientsäkerheten. Det finns dock begränsad forskning på ambulanssjuksköterskans egna erfarenheter av teamarbete och hur de upplever att teamarbetet påverkar patientsäkerheten. Syfte: Syftet med studien var att undersöka ambulanssjuksköterskors upplevelser av samverkan i team och deras erfarenheter av hur teamarbete påverkar patientsäkerheten. Metod: En kvalitativ intervjustudie med induktiv ansats användes. Tio intervjuer med yrkesverksamma ambulanssjuksköterskor genomfördes. Intervjuerna transkriberades för att sedan analyseras enligt Graneheim och Lundmans metod för kvalitativ innehållsanalys. Resultat: Resultatet visade att det fanns faktorer som påverkade hur ambulanssjuksköterskorna upplevde samverkan i teamet. Faktorer som situationsmedvetenhet, kommunikation, kompetens och erfarenhet identifierades. Fanns brister i någon eller flera av de faktorerna påverkades teamet negativt vilket även påverkade patientens omhändertagande negativt. Bland annat tog omhändertagandet längre tid och livsviktig behandling sattes inte in i rätt tid. Teamet påverkades positivt när rollerna i teamet var tydliga och kommunikationen fungerade. När teammedlemmarna hade samma utbildningsnivå ökade tryggheten då de hade liknande förförståelse och liknande sätt att se, bedöma och behandla patienten. Slutsats: Denna studie har visat att patientens omhändertagande påverkas av hur teamarbetet fungerar. Studien kan därför användas som grund för att förbättra teamarbetet inom ambulansen vilket i sin tur skulle förbättra patientsäkerheten