Classification Models

⚠️NOTE⚠️ We are currently in the middle of uploading the weights. All might not be available.

Model	Weights	Acc
ResNet-18	chkpt	79.5
ResNet-50	chkpt	84.6
ResNet-101	chkpt	81.36
MobileNetv3-S	chkpt	80.5
MobileNetv3-L	chkpt	74.67
EffNet-B0	chkpt	83.2
EffNet-B3	chkpt	83.64
EffNet-B5	chkpt	84.5
ConvNeXt-T	chkpt	85.6
ConvNeXt-M	chkpt	85.9
ConvNeXt-L	chkpt	84.7
ViT-T	chkpt	83.43
ViT-B	chkpt	86.4
CaiT-T	chkpt	85.2
CaiT-S	chkpt	86.9
Swin-T	chkpt	85.59
Swin-B	chkpt	85.3
Swin-L	chkpt	87.0
MaxViT-S	chkpt	86.5
MaxViT-B	chkpt	87.08
CoAtNet-1	chkpt	86.1
CoAtNet-3	chkpt	84.3
EffFormer-L1	chkpt	80.5
EffFormer-L3	chkpt	82.7
EffFormer-L7	chkpt	81.2

Pretrained Weights on iNaturalist

ReNet-101	Weights	Acc.
iNat21	✅chkpt	<80%
iNat17	✅chkpt	60.41%

Semantic Segmentation Models

Access dataset via:

• Sugar Beet
• Carrot Weed
• Bean Weed

⚠️NOTE⚠️ We are currently in the middle of uploading the weights. All might not be available.

Model	BeanWeed	SugarBeet	CarrotWeed
UNet	✅72.49 mIOU, chkpt	✅85.47 mIOU, chkpt	✅78.32 mIOU, chkpt
DeepLab v3+	78.03 mIOU, chkpt	86.02 mIOU, chkpt	✅83.16 mIOU, chkpt
OCR	79.51 mIOU, chkpt	87.34 mIOU, chkpt	✅86.53 mIOU, chkpt
SegNext	83.90 mIOU, chkpt	87.65 mIOU, chkpt	✅88.54 mIOU, chkpt

✅MSCAN backbone SegNext

Instances Segmentation Models

Access dataset via:

• PhenoBench
• GrowliFlower

Model	Data	Weights	PQ
MaskRCNN (ResNet-101 FPN backbone)	PhenoBench	✅chkpt	44.05
MaskRCNN (ResNet-101 FPN backbone)	GrowliFlower	✅chkpt	56.33