BreastCancerNet: Flask-Enabled Attention-Driven Hybrid Dual DNN Framework for Real-Time Breast Cancer Prediction.

Breast cancer is the most prevalent cancer among women and poses a significant global health challenge due to its association with uncontrolled cell proliferation. Artificial intelligence (AI) integration into medical practice has shown promise in boosting diagnosis accuracy and treatment protocol optimisation, thus contributing to improved survival rates globally. This paper presents a comprehensive analysis utilizing the Wisconsin Breast Cancer dataset, comprising data from 569 patients and 30 attributes.

Real-Time Abnormal Object Detection for Video Surveillance in Smart Cities.

With the adaptation of video surveillance in many areas for object detection, monitoring abnormal behavior in several cameras requires constant human tracking for a single camera operative, which is a tedious task. In multiview cameras, accurately detecting different types of guns and knives and classifying them from other video surveillance objects in real-time scenarios is difficult. Most detecting cameras are resource-constrained devices with limited computational capacities.