International Journal For Multidisciplinary Research

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SMART VISION: DETECT AND DESCRIBE

Author(s) Mr. MANJUNATHA G, Ms. Kruthi M, Ms. Deekshitha M R, Mr. Kishan B, Ms. Deeksha S K
Country India
Abstract As the field of computer vision evolves rapidly, the need for integrated systems that can perform multi-faceted visual analysis is growing. Conventional recognition systems are usually limited to single-purpose tasks, thus, solutions that are fragmented and lack versatility are the result. This manuscript introduces "Smart Vision: Detect and Describe," a single AI-based visual perception system that is capable of detecting and understanding the most common entities in the real world such as objects, hand gestures, and handwritten digits in real-time. The system in question is employing a modular architecture based on the Flask web framework and it is integrating cutting-edge deep learning models. In particular, it uses YOLOv8 for fast and accurate object detection, while several Convolutional Neural Networks (CNNs) are being employed for gesture and digit recognition. The system, by merging these separate vision problems into one platform, not only facilitates adaptive detection but also can output contextual descriptions via a connected camera. Testing-with data from live streaming and on-the-fly model execution-shows that the system is very accurate and prompt. Such results are an endorsement of the framework, and they open up a plethora of possibilities for the framework to be used in real-world scenarios. Examples of such scenarios include the employment of the technology in developing devices that aid the visually impaired, intelligent robotics, and sophisticated security surveillance systems.
Keywords Computer Vision, Deep Learning, YOLOv8, CNN, Flask, Real-time Detection, Assistive Technology.
Field Engineering
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-12-11
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.62731
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