But do you ever wonder how the deep learning object detection algorithms are evolved over the years, their pros and cons?I find the paper - Recent Advances in Deep Learning for Object Detection a really good answer to this quest. Let me summarize what I have learned, hopefully, elaborate ...
With the wide application of deep learning, the accuracy and efficiency of object detection have been greatly improved. However, object detection based on deep learning still faces challenges such as improving the performance of mainstream object detection algorithms and the detection accuracy of small ...
deep learning algorithms for detection tasks, the performance of object detectors has been greatly improved.In order to understand the main development status of object detection pipeline thoroughly and deeply, in this survey, we analyze the methods of existing typical detection models and describe the...
In intelligent transportation systems, object detection for a surveillance video is one of the important functions. The performance of existing surveillance video object detection algorithms is affected by the conflict between the features of the objects, which leads to a decline in precision. Therefore...
Deep learning is an AI function and a subset of machine learning, used for processing large amounts of complex data. Deep learning can automatically create algorithms based on data patterns. Here are 4,736 public repositories matching this topic... Language: All Sort: Most stars deepfakes ...
Learn algorithms including beam search for speech recognition Study planning, control, and optimization, focusing on stochastic gradient descent. I have to say it again: you’re learning from the best here. Yann LeCun’s reputation in the world of machine learning and deep learning can’t be ...
Whereas YOLO is orders of magnitude faster than other object detection algorithms for intelligent visual surveillance system (IVSS), it struggles to detect small objects within the image. In self-driving cars, YOLO could detect nearby cars with high confidence, but faraway cars that appear small ...
Deep learning is popular for mainly three reasons: 1) powerful central processing unit and high-performance computing devices, 2) large volume of data serves deep learning algorithms, and 3) creative algorithms for neural networks work [107]. Deep learning has brought revolutionary changes duo to ...
Comparing the choice between deep learning or machine learning algorithms for your artificial intelligence application depends on your system’s goals and requirements. Why choose deep learning over machine learning? In one word, accuracy. Deep learning generally achieves higher accuracy and offers more ...
Deep learning algorithms are becoming more popular for IoT applications on the edge because of human-level accuracy in object recognition and classification. Some uses cases are included but not limited to face detection and recognition in security cameras, video classification, speech recognition, real...