Deep Learning and Machine Learning -- Object Detection and Semantic Segmentation: From Theory to Applications
An in-depth exploration of object detection and semantic segmentation is provided, combining theoretical foundations with practical applications. State-of-the-art advancements in machine learning and deep learning are reviewed, focusing on convolutional neural networks (CNNs), YOLO architectures, and transformer-based approaches such as DETR. The integration of artificial intelligence (AI) techniques and large language models for enhancing object detection in complex environments is examined. Additionally, a comprehensive analysis of big data processing is presented, with emphasis on model optimization and performance evaluation metrics. By bridging the gap between traditional methods and modern deep learning frameworks, valuable insights are offered for researchers, data scientists, and engineers aiming to apply AI-driven methodologies to large-scale object detection tasks.
Code (0)
등록된 구현이 없습니다.
Tasks
Deep LearningModel OptimizationObjectobject-detectionObject DetectionSemantic SegmentationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Learning to Cluster for Proposal-Free Instance Segmentation
This work proposed a novel learning objective to train a deep neural network to perform end-to-end image pixel clustering. We applied the approach to instance segmentation, which is at the intersection of image semantic …
Autonomous DrivingClusteringInstance SegmentationLane Detection+4MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features
In this work, we tackle the problem of instance segmentation, the task of simultaneously solving object detection and semantic segmentation. Towards this goal, we present a model, called MaskLab, which produces three out…
Instance SegmentationObjectobject-detectionObject Detection+3Exploiting Depth from Single Monocular Images for Object Detection and Semantic Segmentation
Augmenting RGB data with measured depth has been shown to improve the performance of a range of tasks in computer vision including object detection and semantic segmentation. Although depth sensors such as the Microsoft …
Depth EstimationObjectobject-detectionObject Detection+2Semantic Object Segmentation via Detection in Weakly Labeled Video
Semantic object segmentation in video is an important step for large-scale multimedia analysis. In many cases, however, semantic objects are only tagged at video-level, making them difficult to be located and segmented. …
Objectobject-detectionObject DetectionSegmentation+1Rate-Distortion Theory in Coding for Machines and its Application
Recent years have seen a tremendous growth in both the capability and popularity of automatic machine analysis of images and video. As a result, a growing need for efficient compression methods optimized for machine visi…
Instance Segmentationobject-detectionObject DetectionSemantic Segmentation