In the world, there are many rare and incurable diseases that need to be detected. The manual detection of those diseases requires more cost and time. Autism is one of the main diseases that are increasing at a higher rate and its detection techniques are very challenging. But the early detection of autism can save a patient or increase their lifetime. So this work concentrates on developing machine learning algorithms to detect autism. Our project's main aim is to detect whether the patient is having autism or not. The appropriate dataset is used with eight machine learning algorithm and...
In the world, there are many rare and incurable diseases that need to be detected. The manual detection of those diseases requires more cost and time....
Using deep learning techniques lung ultrasonography (LUS) images are analyzed instead of CT scan images for COVID-19 detection. The severity of the disease is found at the pixel level and frame level. Every pixel of image will be classified with the help of semantic segmentation network, resulting in the detection of COVID part in the input image. When compared to the existing method, this proposed method can give better classification.
Using deep learning techniques lung ultrasonography (LUS) images are analyzed instead of CT scan images for COVID-19 detection. The severity of the di...
Mithilfe von Deep-Learning-Techniken werden Lungenultraschallbilder (LUS) anstelle von CT-Scan-Bildern zur Erkennung von COVID-19 analysiert. Der Schweregrad der Krankheit wird auf Pixel- und Bildebene ermittelt. Jedes Pixel des Bildes wird mit Hilfe eines semantischen Segmentierungsnetzwerks klassifiziert, was zur Erkennung des COVID-Anteils im Eingabebild führt. Im Vergleich zur bestehenden Methode kann diese vorgeschlagene Methode eine bessere Klassifizierung liefern.
Mithilfe von Deep-Learning-Techniken werden Lungenultraschallbilder (LUS) anstelle von CT-Scan-Bildern zur Erkennung von COVID-19 analysiert. Der Schw...
En utilisant des techniques d'apprentissage profond, les images d'échographie pulmonaire (LUS) sont analysées au lieu des images de tomodensitométrie pour la détection du COVID-19. La gravité de la maladie est trouvée au niveau du pixel et de l'image. Chaque pixel de l'image sera classé à l'aide d'un réseau de segmentation sémantique, ce qui permettra de détecter la partie COVID dans l'image d'entrée. Comparée à la méthode existante, la méthode proposée permet une meilleure classification.
En utilisant des techniques d'apprentissage profond, les images d'échographie pulmonaire (LUS) sont analysées au lieu des images de tomodensitométr...
