Faster R-CNN for Robust Pedestrian Detection Using Semantic Segmentation Network

Convolutional neural networks (CNN) have enabled significant improvements in pedestrian detection owing to the strong representation ability of the CNN features. However, it is generally difficult to reduce false positives on hard negative samples such as tree leaves, traffic lights, poles, etc. Some of these hard negatives can be removed by making use of high level semantic vision cues. In this paper, we propose a region-based CNN method which makes use of semantic cues for better pedestrian detection. Our method extends the Faster R-CNN detection framework by adding a branch of network for semantic image segmentation. The semantic network aims to compute complementary higher level semantic features to be integrated with the convolutional features. We make use of multi-resolution feature maps extracted from different network layers in order to ensure good detection accuracy for pedestrians at different scales. Boosted forest is used for training the integrated features in a cascaded manner for hard negatives mining. Experiments on the Caltech pedestrian dataset show improvements on detection accuracy with the semantic network. With the deep VGG16 model, our pedestrian detection method achieves robust detection performance on the Caltech dataset

The study on the integration of Activity Based Costing (ABC) system and six-sigma principle

Manufacturing organizations are facing much more challenges as compared to the earlier years. The important and crucial decisions have to be taken by the management in continuous basis in order to ensure the survival and competitiveness of company throughout the journey to become a successful organization. In order to make these decisions fast and correct, they need more accurate information related to financial and non-financial aspects. The conventional cost management systems, which were developed decades ago are unable to provide all information required to make right decision, justify the cost reduction and process improvements (Chen, 1996). This is because they were based on labor-intensive production system while today’s production processes are more sophisticated and faces constant changes. An alternative costing system, Activity Based Costing (ABC) has emerged to the new solution to costing system. It provides financial and non-financial information not only for product costing but also for each activity of manufacturing process. It can list and measure the cost of each activity individually in production and in supporting activities to deliver of a product or service right to customers (Sohal & Chung, 1998). ABC focuses on the activities performed to produce the products throughout the manufacturing process (Gunasekaran et al., 1999). By assigning other costs, such as marketing and administrative to cost object, ABC able to provide more accurate product costs. It helps to improve the operational performance by allocating overhead costs correctly. It provides cost information based on the actual consumption of the resources by each particular activity. The goal of ABC is to reveal cost allocation information by tracing the production costs accurately to activities and product (Gunasekaran et al., 1999). The implementation of ABC has provided many benefits, such as more accurate product costing, providing of cost behavior information and tracing resources consumptions. Realizing many benefits gain from implementation of ABC, many companies have embarked in applying ABC system. However, there are many problems and barriers they encountered during the implementation, which made some has decided to abort this system and not be able to exploit its advantages. It is the objective of this study to help foster the growth of Malaysian companies by helping them to provide better understanding,knowledge and skills to take advantage of using ABC as a tool to improve their manufacturing process. The title of the project is The Study on Integration of Activity-based Costing and Six-sigma Principle. The specific objective of the study is to determine success factors for ABC implementation in manufacturing companies based on Six-sigma process improvement principle. The focus of the study is to identify and understand the critical success factors in implementation of ABC, to identify and specified the problems and barriers and to understand their relationship with the ABC success. In order to identify, understand and formulate the proposed solution, this study will use a survey approach to get required data for further analysis. The survey will be based on mailed questionnaires to selected manufacturing industries in Malaysia. In order to formulate a comprehensive and relevant set of questionnaires, a comprehensive review of literature will be studied, followed by validation and verification process,which involved expert opinions and a pilot study. The next phase is where data from the study will be analyzed to identify areas related to the level of acceptance of ABC,the critical success factors and also to determine the relationship between the organization’s factors and the success of implementation of ABC system. The tangible outcome of this project is to provide a set of proposed guidelines and support tools for manufacturing organizations in applying Activity-based Costing for process improvement efforts as suggested by Six-sigma improvement principle

Language in the Age of Artificial Intelligence

AI language models can now produce text that is indistinguishable from our own, forcing us into a confrontation with the romantic assumptions underlying ‘natural language’ in the West. In this thesis, I will conduct a genealogy of the ‘natural’ and ‘artificial’ qualities of language through the literary, philosophical, and mathematical texts in which our ideas of authorship are premised. My hope is that this discussion will deepen our understanding of the language produced by AI models, answer why we feel compelled to anthropomorphize these machines, and situate readers in the reality of our present linguistic moment

Robust iris recognition under unconstrained settings

Tese de mestrado integrado. Bioengenharia. Faculdade de Engenharia. Universidade do Porto. 201

Non-ideal iris recognition

Of the many biometrics that exist, iris recognition is finding more attention than any other due to its potential for improved accuracy, permanence, and acceptance. Current iris recognition systems operate on frontal view images of good quality. Due to the small area of the iris, user co-operation is required. In this work, a new system capable of processing iris images which are not necessarily in frontal view is described. This overcomes one of the major hurdles with current iris recognition systems and enhances user convenience and accuracy. The proposed system is designed to operate in two steps: (i) preprocessing and estimation of the gaze direction and (ii) processing and encoding of the rotated iris image. Two objective functions are used to estimate the gaze direction. Later, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. Two methods: (i) PCA and (ii) ICA are used for encoding. Three different datasets are used to quantify performance of the proposed non-ideal recognition system

Document image processing using irregular pyramid structure

Ph.DDOCTOR OF PHILOSOPH

Enumeration of polyhedral graphs

This thesis is concerned with the design of a polyhedron enumeration algorithm. The approach taken focuses on specic classes of polyhedra and their graph theoretic properties. This is then compared more broadly to other graph enumeration algorithms that are concerned with the same or a superset which includes these properties. An original and novel algorithm is contributed to this area. The approach taken divides the problem into prescribed vertex and face degree sequences for the graphs. Using a range of existence, ordered enumeration and isomorphism techniques, it finds all unique 4-regular, 3-connected planar graphs. The algorithm is a vertex addition algorithm which means that each result output at a given stage has a new vertex added. Other results from different stages are never required for further computation and comparison, hence the process is embarrassingly parallel. Therefore, the enumeration can be distributed optimally across a cluster of computers. This work has led to a successfully implemented algorithm which takes a different approach to its treatment of the class of 4-regular, 3-connected planar graphs. As such this has led to observations and theory about other classes of graphs and graph embeddings which relate to this research

Pierre Schaeffers typo-morphology of sonic objects.

SIGLEAvailable from British Library Document Supply Centre- DSC:D174501 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Biometrics

Biometrics uses methods for unique recognition of humans based upon one or more intrinsic physical or behavioral traits. In computer science, particularly, biometrics is used as a form of identity access management and access control. It is also used to identify individuals in groups that are under surveillance. The book consists of 13 chapters, each focusing on a certain aspect of the problem. The book chapters are divided into three sections: physical biometrics, behavioral biometrics and medical biometrics. The key objective of the book is to provide comprehensive reference and text on human authentication and people identity verification from both physiological, behavioural and other points of view. It aims to publish new insights into current innovations in computer systems and technology for biometrics development and its applications. The book was reviewed by the editor Dr. Jucheng Yang, and many of the guest editors, such as Dr. Girija Chetty, Dr. Norman Poh, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park, Dr. Sook Yoon and so on, who also made a significant contribution to the book