Titlebook: Computer Vision and Image Processing; 8th International Co Harkeerat Kaur,Vinit Jakhetiya,Sanjeev Kumar Conference proceedings 2024 The Edi

長(zhǎng)矛

A Simplified 3D Ultrasound Freehand Imaging Framework Using 1D Linear Probe and Low-Cost Mechanicalltrasound volume reconstruction and demonstrate its efficacy with an . tube phantom study and an . bone experiment. The comparison between a sensorless freehand and the proposed mechanical track based acquisition is available online (.).

cliche

,WSD: Wild Selfie Dataset for?Face Recognition in?Selfie Images,n, and alignment. We compare the proposed dataset with existing benchmark datasets in terms of different characteristics. The complexity of WSD dataset is also observed experimentally as compared to the existing face datasets. The dataset can be obtained from ..

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PoseWatch: Advancing Real Time Human Pose Tracking and Juxtaposition with Deep Learning,correctness of the pose by comparing the extracted key points and give feedback to students if any corrections need to be made. The proposed model is trained with 40+ yoga and exercise poses, and evaluated the model’s performance with the mAP, and the model achieved an accuracy of 99.04%. The result

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Finasteride

Enhanced On-Device Video Summarization Using Audio and Visual Features,nts and one has to leverage the resources wisely. In this paper, we present a novel approach which demonstrates a different method to make use of audio features along with visual cues in video summarization. The proposed approach uses different models for inferencing from audio and visual features a

要素

,Fractal-Based Approach to?Secure Key Generation from?Fingerprint and?Iris Biometrics,egions of interest (ROIs) in fingerprint and iris images. The feature vectors from two modalities are then fused to form a single feature vector. A quantization mechanism is applied to generate a stable and unique key. The efficacy of the proposed method was evaluated through a number of experiments

bacteria

,Histogram Matching Based Data-Augmentation and?Its Impact on?CNN Model for?Covid-19 and?Pneumonia DCovid-Lite model respectively, after employing the proposed augmented dataset. Furthermore, we have implemented a popular CNN model i.e., VGG-16 and by the proposed data-augmentation we have achieved the best results of 95% accuracy, 96% F1 score, 96% precision and 96% recall.

periodontitis

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