DEVELOPMENT OF A DEEP LEARNING-BASED MOBILE APPLICATION TO DETECT FRESHNESS OF FRUITS

Fruits play a crucial role in our diet as they contain nutrients that are vital for our health. These nutrients are important as they help us protect against chronic diseases. Fruits that are not fresh will not contain as many nutrients than when it was fresh. Thus, it is important to ensure that...

Täydet tiedot

Tallennettuna:

Bibliografiset tiedot
Päätekijä:	SALEM ABO EYADA, SHADIA TALAL
Aineistotyyppi:	Opinnäyte
Kieli:	englanti
Julkaistu:	Department of Computer Science and Engineering, MIST 2024
Linkit:	http://dspace.mist.ac.bd:8080/xmlui/handle/123456789/804
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!

Samankaltaisia teoksia: DEVELOPMENT OF A DEEP LEARNING-BASED MOBILE APPLICATION TO DETECT FRESHNESS OF FRUITS

Pikavilkaisu
DEVELOPMENT OF A DEEP LEARNING-BASED MOBILE APPLICATION TO DETECT FRESHNESS OF FRUITS /
Pikavilkaisu
RETINAL OCT DISEASE DETECTION BY IMAGE-BASED DEEP LEARNING /
Pikavilkaisu
A DEEP LEARNING-BASED APPROACH FOR DETECTING BANGLA SPAM EMAILS /
Pikavilkaisu
Deep learning /
Pikavilkaisu
AN ADVERSARIAL APPROACH FOR INTRUSION DETECTION USING DEEP LEARNING /
Pikavilkaisu
VISION TRANSFORMER-BASED DEEP LEARNING TECHNIQUES FOR IMPROPER FACE MASK-WEARING DETECTION /
Pikavilkaisu
Deep learning with python /
Pikavilkaisu
DESIGN AND DEVELOPMENT OF A MOBILE APPLICATION FOR IDENTIFYING INTOXICATED PEOPLE BASED ON SITUATIONAL IMPAIRMENT /
Pikavilkaisu
FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD
Pikavilkaisu
FLOW BASED ANOMALY DETECTION IN SOFTWARE DEFINED NETWORKING: A DEEP LEARNING APPROACH WITH FEATURE SELECTION METHOD /
Pikavilkaisu
MULTI-CLASS BREAST CANCER DETECTION USING DEEP LEARNING AND QUANTUM ANNEALING-BASED HYPERPARAMETER OPTIMIZATION /
Pikavilkaisu
DETECTING DDOS ATTACKS USING MACHINE LEARNING & DEEP LEARNING APPROACHES WITH A COMPANION VISUALIZATION DASHBOARD /
Pikavilkaisu
FLOOD DETECTION AND FLOODED AREA SEGMENTATION USING ENSEMBLE MACHINE LEARNING AND DEEP LEARNING APPROACHES /
Pikavilkaisu
A DEEP LEARNING-BASED STACKING APPROACH FOR SKIN ALLERGY CLASSIFICATION /
Pikavilkaisu
DEEP LEARNING BASED MULTIPLE OBJECT DETECTION AND DISTANCE MANAGEMENT FROM CUSTOM-BUILT DATASET WITH HETEROGENIOUS TRAFFIC /
Pikavilkaisu
DESIGN AND IMPLEMENTATION OF A MOBILE-BASED MICROSCOPIC SYSTEM FOR BIOMEDICAL APPLICATION /
Pikavilkaisu
USER CENTRED DESIGN (UCD) BASED PRIVACY AND SECURITY FRAMEWORK FOR DEVELOPING MOBILE HEALTH APPLICATIONS /
Pikavilkaisu
Analyzing the Performance of Deep Learning Models for Detecting Hate Speech on Social Media Platforms
Pikavilkaisu
EXPLORING DEEP LEARNING ALGORITHMS FOR DETECTION AND PREDICTION OF WATER BODIES USING SATELLITE IMAGES /
Pikavilkaisu
STACKED ATTENTION BASED DEEP LEARNING MODEL FOR VIDEO CAPTIONING IN BENGALI /
Pikavilkaisu
EARTHQUAKE MAGNITUDE PREDICTION USING MACHINE LEARNING AND DEEP LEARNING /
Pikavilkaisu
DEVELOPMENT OF MOBILE ROBOT FOR SURVEILLANCE AND MONITORING /
Pikavilkaisu
DEVELOPMENT OF AN ACCELEROMETER-BASED EPILEPTIC SEIZURE DETECTION DEVICE /
Pikavilkaisu
DEEP REINFORCEMENT LEARNING BASED OPTIMAL COMPUTATION OFFLOADING IN FOG COMPUTING ENVIRONMENT /