Research

In this research, we initiated a unique and cutting-edge backbone neural network for the conventional YOLO algorithm which we named as SBHK-Net. The network boosted up the performance of the existing YOLO algorithm drastically which manifests a strong potential of improving tracking and recognition accuracies of other conventional algorithms in the robot vision industry as well. It has the greatest accuracy 59.2% AP among all known real-time object detectors with 30 FPS or above on GPU RTX3060, and it outperforms all other known object detectors in the range of 5 FPS to 160 FPS.

We focused upon the deep learning approach to classify the normal and abnormal breast according to the medical imaging from the MIAS dataset of Mammograms and Pixel Intensity. The Convolution Neural Network (CNN) alongside ResNet, AmoebaNet and EfficientNet have been used for the detection with 330 mammograms in which 194 images are normal and 136 are having the identification of abnormal breasts.

In this research, we focused mostly on our rigorous novel implementations and iterative result analysis of different cutting-edge modified versions of EfficientNet architectures namely EfficientNet-V1 (b0-b7) and EfficientNet-V2 (b0-b3) with ultrasound image, named as CEIMVEN. We utilized transfer learning approach here for using the pre-trained models of EfficientNet versions.

Nano Rover is a significant approach of cost-efficient surveillance and reconnaissance robot which is fully functional and cost-efficient at the same time. It features the service of active reconnaissance mode with LIDAR sensor, location tracking with GPS Neo 6M module, visual information collection, person detection, weapons detection and identification, gender and age prediction of the hostile and other artificial threat detection, etc.

This robotics research project proposes a solution which appears to be a full-fledged Bluetooth controlled Submarine prototype with a sensory chipboard attached inside its endo-skeleton which contains multiple sensors like DHT11 temperature-humidity, dust, CO2 and YL69 pH sensors. The sensory data provides the information of underwater whether the naval environment is habitable for the marine biological species or not, under the terrible effect of global climate change.

In this research, we tried to represent an optimized implementation of different chatbot algorithmic approaches within a single University Automation query platform where the previous chatbots were developed concerning the utility areas of agriculture, economics, medical science with disease prediction, admission system and tourism.

In the rural world of medical services, we generally notice a lot of havoc which generally happens in the hospitals, clinics and related other medical centers. The conditions of Intensive Care Units (ICU) of the rural areas are quite intolerable because of the lack of qualified nurses. This study aims to minimize the hazard at the highest accuracy level possible.