Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Neha Sharma,Amol C. Goje,Alfred M. Bruckstein Conference proceedings 2024 T

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寵愛(ài)

esearchers because of poor visual clarity. Further, in densely populated areas, the low contrast of the built-up areas causes huge difficulty in the detection of roof-tops individually. In view of such challenges, we develop a Mask-RCNN model for segmentation of probable built-up areas in low-resolu

完全

o test the performance of our proposed system, we used several machine learning algorithms like Support Vector Machines (SVMs) and Random Forest (RF) algorithms. Here, these algorithms are mainly used for diagnosing mental health disorders on the basis of given input (i.e. verified dataset of sympto

老巫婆

two main stages: feature extraction and speech recognition. The feature extraction stage involves the use of the VGGish model to process the raw audio signals and create a feature representation that is both concise and comprehensive. The resulting feature vectors capture various acoustic attribute

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陳舊

g pothole detection model, built upon YOLO V8, has been proposed. Additionally, road quality and PHR mapping via sensory data (accelerometer and gyrometer), which undergoes post-processing to provide quality observations for various vehicles and classify them, has been introduced. Leveraging this da

陳舊

learning-based 3D facial reconstruction algorithm with motion capture data to produce high-quality facial animation. We evaluate our method by comparing it to traditional animation methods and show that our approach produces more realistic and natural facial expressions. Our results demonstrate the

ANA

,An revolution?re Traditionen anknüpfen,inopathy (NPDR), or proliferative diabetic retinopathy (PDR), from a healthy eyeball to a proliferative diabetic retinopathy presence. Remarkably, our approach attains an impressive 93.5% accuracy, bolstering the model‘s reliability in diabetic retinopathy diagnosis from fundus images. With potentia

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