Podobne zapisy: MACHINE LEARNING BASED SEPSIS PREDICTION FOR FOOT INFECTION IN DIABETIC PATIENTS /
- PREDICTING POLYCYSTIC OVARY SYNDROME THROUGH MACHINE LEARNING TECHNIQUE USING PATIENTS' SYMPTOM DATA AND OVARY ULTRASOUND IMAGES /
- AI-BASED MEDICATION ASSISTIVE SYSTEM WITH INSULIN DOSE PREDICTION FOR ELDERLY DIABETIC PATIENT /
- PREDICTION OF URINARY TRACT INFECTIONS USING HMM
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- DIABETIC RETINOPATHY STAGE DETECTION USING RETINAL FUNDUS IMAGES THROUGH ENSEMBLE LEARNING APPROACH/
- MACHINE LEARNING MODEL TO DETECT PNEUMONIA OF COVID-19 PATIENTS FROM CHEST X-RAY IMAGES /
Temat: Computer Science and Engineering
- PREDICTION OF URINARY TRACT INFECTIONS USING HMM
- MOBILE VIDEO TRANSMITTING ROBOT /
- PARAMETRIC STUDY OF STUDENT LEARNING IN IT USING DATA MINING
- MULTI LAYER NEURAL NETWORK BASED AUTOMATIC WORD RECOGNITION FOR BANGLA SPOKEN LANGUAGE /
- INTER WORD SEMANTIC AND STRING DISTANCE USING ONTOLOGICAL TECHNIQUES /
- USER SESSION BASED AUTOMATED TEST CASE GENERATION USING NEUMATIC ALGORITHM /
Temat: This Thesis paper of CSE in M.Sc. program
- SENTIMENT ANALYSIS OF MULTI-REGIONAL AND MULTILINGUAL TRENDING YOUTUBR VIDEOS USING A MODIFIED DEEP LEARNING MODEL /
- DEVELOPMEMENT OF A MACHINE LEARNING MODEL FOR BILLINGUAL SMS SPAM DETECTION /
- MACHINE LEARNING BASED SEPSIS PREDICTION FOR FOOT INFECTION IN DIABETIC PATIENTS /
- PERFORMANCE ANALYSIS OF PATH PLANNING ALGORITHMS FOR MOBILE ROBOT NAVIGATION BASED ON A GRAPHICAL SIMULATION PLATFORM /
- PHYLOGENETIC-INFORMED GRAPH NEURAL NETWORK FOR DRUG REPOSITIONING /
Autor: Tasneem, Zareen
Autor: Supervised by Dr. Md. Shohrab Hossain
- IDENTIFICATION OF DDOS ATTACK THROUGH INTRUSION DETECTION MODEL USING ENSEMBLE MACHINE LEARNING /
- MACHINE LEARNING MODEL TO DETECT PNEUMONIA OF COVID-19 PATIENTS FROM CHEST X-RAY IMAGES /
- STATIC ANALYSIS BASED MALWARE DETECTION FOR ZERO-DAY ATTACKS IN ANDROID APPLICATIONS /
- MACHINE LEARNING BASED SEPSIS PREDICTION FOR FOOT INFECTION IN DIABETIC PATIENTS /
- DEVELOPMENT OF A TASK MANAGEMENT SYSTEM FOR SMALL AND MEDIUM SIZED ENTERPRISES /
- DEVELOPMENT OF HUMAN RESOURCE MANAGEMENT SYSTEM FOR SMALL SCALE SOFTWARE COMPANY /