RETINAL VESSEL SEGMENTATION USING MODIFIED U-NET MODEL /

Tallennettuna:

Bibliografiset tiedot
Päätekijä:	KAMAL, ELMA SHUMSUN
Yhteisötekijä:	Supervised by Nusrat Sharmin (Associate Professor, Dept of CSE, MIST)
Aineistotyyppi:	Kirja
Kieli:	englanti
Julkaistu:	Dhaka : CSE DEPT, MIST. c2025.
Aiheet:	Computer Science and Engineering This Thesis Paper of CSE in M.Sc Program.
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

Samankaltaisia teoksia: RETINAL VESSEL SEGMENTATION USING MODIFIED U-NET MODEL /

Pikavilkaisu
DIABETIC RETINOPATHY STAGE DETECTION USING RETINAL FUNDUS IMAGES THROUGH ENSEMBLE LEARNING APPROACH/
Pikavilkaisu
COLORECTAL CANCER HISTOPATHOLOGY SEGMENTATION AND CLASSIFICATION THROUGH DISTILLED MOBILENETV2 U-NET AND SWIN TRANSFORMER PIPELINE /
Pikavilkaisu
SENTIMENT ANALYSIS OF MULTI-REGIONAL AND MULTILINGUAL TRENDING YOUTUBR VIDEOS USING A MODIFIED DEEP LEARNING MODEL /
Pikavilkaisu
ISCHEMIC STROKE LESION SEGMENTATION FROM DIFFUSION-WEIGHTED MRI USING DEEP ENSEMBLE LEARNING / /
Pikavilkaisu
BANGLA HATE SPEECH DETECTION ON SOCIAL MEDIA USING MACHINE LEARNING MODEL/
Pikavilkaisu
IDENTIFICATION OF DDOS ATTACK THROUGH INTRUSION DETECTION MODEL USING ENSEMBLE MACHINE LEARNING /
Pikavilkaisu
DESIGN AND DEVELOPMENT OF A MULTI-CHANNEL MILITARY APPLICATION USING INTERACTIVE DIALOGUE MODEL (IDM) PROVIDING ENHANCED USABILITY /
Pikavilkaisu
DEVELOPMEMENT OF A MACHINE LEARNING MODEL FOR BILLINGUAL SMS SPAM DETECTION /
Pikavilkaisu
FINE-TUNED U-NET VARIATS WITH EXTENDED ARCHITECTURE FOR ENHANCED MICROSCOPIC IMAGE SEGMENTATION /
Pikavilkaisu
MACHINE LEARNING MODEL TO DETECT PNEUMONIA OF COVID-19 PATIENTS FROM CHEST X-RAY IMAGES /
Pikavilkaisu
AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
Pikavilkaisu
HYBRID AI MODEL INTEGRATING DEEP LEARNING AND FUZZY LOGIC FOR TOMATO LEAF DISEASE DETECTION AND SEVERITY ESTIMATION /
Pikavilkaisu
PREDICTION OF POTATO DISEASE FROM LEAVES USING DEEP LEARNING /
Pikavilkaisu
MACHINE LEARNING APPROACHES FOR THE DETECTION OF LUNG CANCER USING MRI IMAGES /
Pikavilkaisu
SENTIMENT ANALYSIS OF COVID-19 TWEETS USING MACHINE LEARNING TECHNIQUES /
Pikavilkaisu
DEVELOPMENT OF AN APPLICATION SOFTWARE FOR SALES PREDICTION USING MACHINE LEARNING ALGORITHMS /
Pikavilkaisu
IDENTIFICATION OF BREST TUMOR FROM MRI IMAGES USING MACHINE LEARNING APPROACHES /
Pikavilkaisu
INTERACTIVE HANDWRITTEN BANGLA DIGIT RECOGNITION SYSTEM USING CONVOLUTIONAL NEURAL NETWORK /
Pikavilkaisu
DETECTING THE FETAL HEALTH CONDITION USING FEDERATED LEARNING APPROACH WITH INCENTIVE-BASED REWARDS SYSTEM /
Pikavilkaisu
SIMILARITY ESTIMATION OF DNA SEQUENCES USING GRAYSCALE IMAGE ENCODING SCHEME ON 2D GRAPHMAP /
Pikavilkaisu
MULTI-CLASS BREAST CANCER DETECTION USING DEEP LEARNING AND QUANTUM ANNEALING-BASED HYPERPARAMETER OPTIMIZATION /
Pikavilkaisu
PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS' SYMPTOM DATA AND OVARY ULTRASOUND IMAGES /
Pikavilkaisu
ROTATION INVARIANT SEGMENTATION OF BANGLA CHARACTERS /
Pikavilkaisu
ROBUST OBJECT SEGMENTATION USING MODIFICATION OF CLASSICAL SPLIT AND MERGE ALGORITHM /