Sign language is a powerful form of communication for humans, and advancements in computer vision systems are driving significant progress in sign language recognition. In the context of Indian sign language (ISL), ea...
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Early and accurate detection of breast cancer, particularly Invasive Ductal Carcinoma (IDC), is critical for improving patient outcomes. Traditional diagnostic methods like histopathology and mammography have limitati...
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Duplicate video files consume valuable storage capacity. Video deduplication removes needless redundancy, to reclaim the storage space and provides an affordable solution that lowers long-term operating expenses. The ...
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This manuscript deems the proposal over utilization of computer digitized vision over the gesture recognition. Gesture language is a language that determines the requirement over combining the finger gesture, its orie...
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ISBN:
(纸本)9798331534950
This manuscript deems the proposal over utilization of computer digitized vision over the gesture recognition. Gesture language is a language that determines the requirement over combining the finger gesture, its orientation, arm and hand movement, facial & body expression that simultaneously explores and advertises the people thoughts. The digital camera makes the recording of live motion streams of pictures with which the acquisition of image is made with the assistance of interface. The training of system is made over each sort of Figureureureureure gestures as representing (5,4,3,2 or 1) atleast in a single time. Later on, the test symbol is delivered and the system makes a try for detecting it. In this proposed study the detection of Figureureureureure gestures is made using the strategy of image processing. The system makes the detection of cumulative finger count. Later on, it makes the identification of individual fingers above the palm. During the processing, it initially makes the detection of skin tone (Color) from the acquired image by the utilization of filter. The image is allowed to process through subsequent steps in order to depict the correct count of fingers. The model makes the detection over the nearer point from the threshold value. The detection of image is made as per the centroid value. Later on, the implication of certain steps is made for enhancing the normal image to an efficient image so that the exposure of fingers is made. Finally, the model makes the detection and decides the finger count and advertises the calculation to the tester. As a result, the classification is done using artificial neural networks based on the previously formulated training model that has been built and realized with more than 92.5% of accuracy in the finger gesture recognition. In this study, the comparison has also been enumerated with other state of art algorithms designed by many researchers. The classification has been illustrated with diagonal sum algori
Medicinal plant identification is essential for holistic treatment systems, where accurate taxonomy ensures the safe and effective use of therapeutic properties. However, traditional methods often struggle with high f...
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This research explores the application of neural networks to improve the resolution of 3D human images. While existing methods have focused on real-time applications, they often fall short in reconstructing high-resol...
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In this paper,Modified Multi-scale Segmentation Network(MMU-SNet)method is proposed for Tamil text *** texts from digi-tal writing pad notes are used for text *** words recognition for texts written from digital writi...
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In this paper,Modified Multi-scale Segmentation Network(MMU-SNet)method is proposed for Tamil text *** texts from digi-tal writing pad notes are used for text *** words recognition for texts written from digital writing pad through text file conversion are challen-ging due to stylus pressure,writing on glass frictionless surfaces,and being less skilled in short writing,alphabet size,style,carved symbols,and orientation angle *** pressure on the pad changes the words in the Tamil language alphabet because the Tamil alphabets have a smaller number of lines,angles,curves,and *** small change in dots,curves,and bends in the Tamil alphabet leads to error in recognition and changes the meaning of the words because of wrong alphabet ***,handwritten English word recognition and conversion of text files from a digital writing pad are performed through various algorithms such as Support Vector Machine(SVM),Kohonen Neural Network(KNN),and Convolutional Neural Network(CNN)for offline and online alphabet *** proposed algorithms are compared with above algorithms for Tamil word *** proposed MMU-SNet method has achieved good accuracy in predicting text,about 96.8%compared to other traditional CNN algorithms.
Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communi...
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Autism spectrum disorder(ASD)can be defined as a neurodevelopmental condition or illness that can disturb kids who have heterogeneous characteristics,like changes in behavior,social disabilities,and difficulty communicating with *** tracking(ET)has become a useful method to detect *** vital aspect of moral erudition is the aptitude to have common visual *** eye-tracking approach offers valuable data regarding the visual behavior of children for accurate and early ***-tracking data can offer insightful information about the behavior and thought processes of people with ASD,but it is important to be aware of its limitations and to combine it with other types of data and assessment techniques to increase the precision of ASD *** operates by scanning the paths of eyes for extracting a series of eye projection points on images for examining the behavior of children with *** purpose of this research is to use deep learning to identify autistic disorders based on eye *** Chaotic Butterfly Optimization technique is used to identify this specific ***,this study develops an ET-based Autism Spectrum Disorder Diagnosis using Chaotic Butterfly Optimization with Deep Learning(ETASD-CBODL)*** presented ETASDCBODL technique mainly focuses on the recognition of ASD via the ET and DL *** accomplish this,the ETASD-CBODL technique exploits the U-Net segmentation technique to recognize interested *** addition,the ETASD-CBODL technique employs Inception v3 feature extraction with CBO algorithm-based hyperparameter ***,the long-shorttermmemory(LSTM)model is exploited for the recognition and classification of *** assess the performance of the ETASD-CBODL technique,a series of simulations were performed on datasets from the figure-shared data *** experimental values of accuracy(99.29%),precision(98.78%),sensitivity(99.29%)and specificity(99.29%)showed a better perfo
Birds are nice-looking from their aesthetic looks and life styles, around 50 billion of birds are living on the earth where some birds are in threat of extinction. For people, distinguishing and classification of bird...
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Parkinson's disease, a neurological disorder which affects the nervous system, manifests as unintentional and uncontrollable movements in the body. With over 6 million individuals globally affected, early detectio...
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