MACHINE LEARNING APPROACHES FOR THE DETECTION OF LUNG CANCER USING MRI IMAGES /

Tallennettuna:

Bibliografiset tiedot
Päätekijä:	Rahman, Md. Mokhlesur
Yhteisötekijä:	Supervised by Dr. T. M. Shahriar Sazzad (Asst. Professor, Dept of CSE, MIST)
Aineistotyyppi:	Kirja
Kieli:	englanti
Julkaistu:	Dhaka : CSE DEPT. MIST, c2024.
Aiheet:	Computer Science and Engineering. This Thesis Paper of CSE in M.Sc. Program.
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

Samankaltaisia teoksia: MACHINE LEARNING APPROACHES FOR THE DETECTION OF LUNG CANCER USING MRI IMAGES /

Pikavilkaisu
DETECTION OF BRAIN TUMORS FROM MRI IMAGES USING MACHINE LEARNING APPROACHES /
Pikavilkaisu
IDENTIFICATION OF BREST TUMOR FROM MRI IMAGES USING MACHINE LEARNING APPROACHES /
Pikavilkaisu
AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
Pikavilkaisu
MULTI-CLASS BREAST CANCER DETECTION USING DEEP LEARNING AND QUANTUM ANNEALING-BASED HYPERPARAMETER OPTIMIZATION /
Pikavilkaisu
DIABETIC RETINOPATHY STAGE DETECTION USING RETINAL FUNDUS IMAGES THROUGH ENSEMBLE LEARNING APPROACH/
Pikavilkaisu
MACHINE LEARNING MODEL TO DETECT PNEUMONIA OF COVID-19 PATIENTS FROM CHEST X-RAY IMAGES /
Pikavilkaisu
ISCHEMIC STROKE LESION SEGMENTATION FROM DIFFUSION-WEIGHTED MRI USING DEEP ENSEMBLE LEARNING / /
Pikavilkaisu
DETECTION OF RICE LEAF BLAST DISEASE THROUGH IMAGE PROCESSING AND MACHINE LEARNING APPROACHES /
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
DETECTING THE FETAL HEALTH CONDITION USING FEDERATED LEARNING APPROACH WITH INCENTIVE-BASED REWARDS SYSTEM /
Pikavilkaisu
DEVELOPMEMENT OF A MACHINE LEARNING MODEL FOR BILLINGUAL SMS SPAM DETECTION /
Pikavilkaisu
SENTIMENT ANALYSIS OF COVID-19 TWEETS USING MACHINE LEARNING TECHNIQUES /
Pikavilkaisu
PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS' SYMPTOM DATA AND OVARY ULTRASOUND IMAGES /
Pikavilkaisu
TOWARDS EVELOPING AN IMAGING APPLICATION TO AID PHYSICIANS ANALYZING MRI IMAGES OF BRAIN TUMOR: A MACHINE LEARNING APPROACH THROUGH COMPARATIVE ANALYSIS /
Pikavilkaisu
DEVELOPMENT OF AN APPLICATION SOFTWARE FOR SALES PREDICTION USING MACHINE LEARNING ALGORITHMS /
Pikavilkaisu
FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD /
Pikavilkaisu
CONVOLUTIONAL NEURAL NETWORK (CNN) FOR DETECTION OF PROSTATE CANCER USING CELL SLIDE IMAGES /
Pikavilkaisu
DEVELOPMENT OF A DEEP LEARNING-BASED MOBILE APPLICATION TO DETECT FRESHNESS OF FRUITS /
Pikavilkaisu
A FEDERATED LEARNING AIDED SYSTEM FOR CLASSIFYING CERVICAL CANCER USING PAP-SMEAR IMAGES/
Pikavilkaisu
FLOOD DETECTION AND FLOODED AREA SEGMENTATION USING ENSEMBLE MACHINE LEARNING AND DEEP LEARNING APPROACHES /
Pikavilkaisu
APPLICATION OF MACHINE LEARNING IN SORTING NANO PARTICLES CHARACTERIZED BY OPTICAL FORCE /
Pikavilkaisu
MACHINE LEARNING BASED SEPSIS PREDICTION FOR FOOT INFECTION IN DIABETIC PATIENTS /
Pikavilkaisu
AUTOMATED IMAGE PROCESSING APPROACH TO DETECT ECTOPIC PREGNANCY USING ULTRASOUND IMAGES /