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Titlebook: Computer Vision and Image Processing; 7th International Co Deep Gupta,Kishor Bhurchandi,Sanjeev Kumar Conference proceedings 2023 The Edito

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樓主: Radiofrequency
51#
發(fā)表于 2025-3-30 11:56:31 | 只看該作者
,A Segmentation Based Robust Fractional Variational Model for?Motion Estimation,, the presented model provides a generalization of integer order derivative based variational functionals and offers an enhanced robustness against outliers while preserving the discontinuity in the dense flow field. The motion is estimated in the form of optical flow. For this purpose, a level set
52#
發(fā)表于 2025-3-30 12:37:57 | 只看該作者
53#
發(fā)表于 2025-3-30 18:05:11 | 只看該作者
,CT Image Synthesis from?MR Image Using Edge-Aware Generative Adversarial Network,omy and the human body’s physiological processes. Radiotherapy planning requires the use of CT as well as MR images. The high radiation exposure of CT and the cost of acquiring multiple modalities motivate a reliable MRI-to-CT synthesis. The MRI-to-CT synthesiser introduced in this paper implements
54#
發(fā)表于 2025-3-30 23:34:19 | 只看該作者
Modified Scaled-YOLOv4: Soccer Player and Ball Detection for Real Time Implementation,ootball, and the passage of the football from one player to another, as well as significant interference between the football and players. Moreover, the diminished pixel resolution of players that are farther away and smaller in the frame in football matches, and the high velocity of the ball, will
55#
發(fā)表于 2025-3-31 01:51:43 | 只看該作者
,CandidNet: A Novel Framework for?Candid Moments Detection,atural head pose, body pose, eye gaze, facial expressions, human-object interactions, and background understanding is not a trivial task. It requires the timing and intuition of a professional photographer to capture fleeting moments. We propose a novel and real-time framework for detecting a candid
56#
發(fā)表于 2025-3-31 07:22:32 | 只看該作者
57#
發(fā)表于 2025-3-31 12:56:27 | 只看該作者
Single Image Dehazing Using Multipath Networks Based on Chain of U-Nets,ed outdoors are seriously degraded in color and contrast due to extreme weather conditions like fog, haze, snow and rain. This poor visual quality can inhibit the performance, which is intended to operate on clear conditions like object detection. In recent years, single-image dehazing, which recove
58#
發(fā)表于 2025-3-31 14:06:04 | 只看該作者
59#
發(fā)表于 2025-3-31 20:52:53 | 只看該作者
60#
發(fā)表于 2025-4-1 01:41:40 | 只看該作者
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