4 research outputs found
Voice Recognition Robot with Real-Time Surveillance and Automation
Voice recognition technology enables the execution of real-world operations
through a single voice command. This paper introduces a voice recognition
system that involves converting input voice signals into corresponding text
using an Android application. The text messages are then transmitted through
Bluetooth connectivity, serving as a communication platform. Simultaneously, a
controller circuit, equipped with a Bluetooth module, receives the text signal
and, following a coding mechanism, executes real-world operations. The paper
extends the application of voice recognition to real-time surveillance and
automation, incorporating obstacle detection and avoidance mechanisms, as well
as control over lighting and horn functions through predefined voice commands.
The proposed technique not only serves as an assistive tool for individuals
with disabilities but also finds utility in industrial automation, enabling
robots to perform specific tasks with precision.Comment: 6 pages, 16 figure
Text Summarization Using Large Language Models: A Comparative Study of MPT-7b-instruct, Falcon-7b-instruct, and OpenAI Chat-GPT Models
Text summarization is a critical Natural Language Processing (NLP) task with
applications ranging from information retrieval to content generation.
Leveraging Large Language Models (LLMs) has shown remarkable promise in
enhancing summarization techniques. This paper embarks on an exploration of
text summarization with a diverse set of LLMs, including MPT-7b-instruct,
falcon-7b-instruct, and OpenAI ChatGPT text-davinci-003 models. The experiment
was performed with different hyperparameters and evaluated the generated
summaries using widely accepted metrics such as the Bilingual Evaluation
Understudy (BLEU) Score, Recall-Oriented Understudy for Gisting Evaluation
(ROUGE) Score, and Bidirectional Encoder Representations from Transformers
(BERT) Score. According to the experiment, text-davinci-003 outperformed the
others. This investigation involved two distinct datasets: CNN Daily Mail and
XSum. Its primary objective was to provide a comprehensive understanding of the
performance of Large Language Models (LLMs) when applied to different datasets.
The assessment of these models' effectiveness contributes valuable insights to
researchers and practitioners within the NLP domain. This work serves as a
resource for those interested in harnessing the potential of LLMs for text
summarization and lays the foundation for the development of advanced
Generative AI applications aimed at addressing a wide spectrum of business
challenges.Comment: 4 pages, 2 table
Histopathologic Cancer Detection
Early diagnosis of the cancer cells is necessary for making an effective
treatment plan and for the health and safety of a patient. Nowadays, doctors
usually use a histological grade that pathologists determine by performing a
semi-quantitative analysis of the histopathological and cytological features of
hematoxylin-eosin (HE) stained histopathological images. This research
contributes a potential classification model for cancer prognosis to
efficiently utilize the valuable information underlying the HE-stained
histopathological images. This work uses the PatchCamelyon benchmark datasets
and trains them in a multi-layer perceptron and convolution model to observe
the model's performance in terms of precision, Recall, F1 Score, Accuracy, and
AUC Score. The evaluation result shows that the baseline convolution model
outperforms the baseline MLP model. Also, this paper introduced ResNet50 and
InceptionNet models with data augmentation, where ResNet50 is able to beat the
state-of-the-art model. Furthermore, the majority vote and concatenation
ensemble were evaluated and provided the future direction of using transfer
learning and segmentation to understand the specific features.Comment: 5 pages, 5 figures, 2 table
Email Based Global Automation with Raspberry Pi and Control Circuit Module: Development of Smart Home Application
Global Automation is an emerging technology of today's era and is based on Internet of Things (IoT). Global automation deals with the controlling of electrical appliances throughout the world. The fabrication of this system has been carried out with interfacing an electrical control system module to Raspberry Pi. An electrical control system module includes a relay driver mechanism through which appliances are controlled automatically in respective condition. In this research project, one email ID has been assigned to Raspberry Pi, and the users from different location having different email ID can mail to Raspberry Pi on assigned email address "[email protected]" with subject heading "Device Control" with predefined command on compose email line. Also, a notification regarding current working condition of this system has been updated on respective user email ID. This approach is an innovative way of implementing smart automation system through which a user can control their electrical appliances like light, fan, television, refrigerator, etc. in their home with the use of email facility. The development of this project helps to enhance the concept of smart home application as well as industrial automation