The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned convolutional neural network to determine a level of crop residue for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.

The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned crop residue classification model to determine a crop residue parameter value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. Furthermore, principal components analysis, such as projecting image patches onto Eigen-images, can be performed to reduce the dimensionality of the feature vector provided to the classification model.

The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned crop residue classification model to determine a crop residue parameter value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. Furthermore, principal components analysis, such as projecting image patches onto Eigen-images, can be performed to reduce the dimensionality of the feature vector provided to the classification model.

The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned semantic segmentation model to determine a crop residue parameter value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.

The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned semantic segmentation model to determine a crop residue parameter value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.

An agricultural machine for processing cut plants to be moved in a progression's direction, the machine includes a chassis fitted with a hitching device enabling it to be hitched to the tractor vehicle, multiple rotors equipped with raking teeth that can be driven in rotation around substantially vertical driving axes distributed on either side of a median plane passing through the chassis. Each outer rotor and the penultimate rotor adjacent to it, driven in opposite rotational directions, form a module of which a longitudinal plane contains the driving axis of the outer rotor and the driving axis of the penultimate rotor, and, in work configuration, the longitudinal plane of a first module forms, together with the median plane, an acute work angle that is open to the rear, and the longitudinal plane of a second module forms an acute work angle with the median plane open to the rear.

An agricultural machine for processing cut plants to be moved in a progression's direction, the machine includes a chassis fitted with a hitching device enabling it to be hitched to the tractor vehicle, multiple rotors equipped with raking teeth that can be driven in rotation around substantially vertical driving axes distributed on either side of a median plane passing through the chassis. Each outer rotor and the penultimate rotor adjacent to it, driven in opposite rotational directions, form a module of which a longitudinal plane contains the driving axis of the outer rotor and the driving axis of the penultimate rotor, and, in work configuration, the longitudinal plane of a first module forms, together with the median plane, an acute work angle that is open to the rear, and the longitudinal plane of a second module forms an acute work angle with the median plane open to the rear.

Unique self-propelled soil working machines are disclosed. In certain exemplary embodiments the self propelled soil working machine includes a tool carrier which is actively adjustable to provide variable downward force on a soil working tool via a suspension element which is further passively responsive to accommodate motion of the tool in response to external force. In certain exemplary embodiments, the tool carrier is configured to adjust the working depth and pitch of the tool. Further embodiments, forms, objects, features, advantages, aspects, and benefits shall become apparent from the following description and figures.

An agricultural implement includes a frame having a longitudinal axis and laterally opposed sides and motive supports mounted to and supporting the frame. The agricultural implement further includes a first wing carried by the frame and at least one second wing, in which each second wing is pivotably connected to the first wing. The agricultural implement also includes an elevator mechanism configured to raise and lower the first wing and the second wing. Each second wing is connected to the first wing by a wing pivot assembly that includes a skewed hinge pivotably connecting one of the second wings to the first wing. The wing pivot assembly allows each second wing to pivot with respect to the first wing between an operating position and a transport position, in which the skewed hinge defines a first pivot axis oriented at an acute angle with respect to the longitudinal axis.

An agricultural implement includes a frame having a longitudinal axis and laterally opposed sides and motive supports mounted to and supporting the frame. The agricultural implement further includes a first wing carried by the frame and at least one second wing, in which each second wing is pivotably connected to the first wing. The agricultural implement also includes an elevator mechanism configured to raise and lower the first wing and the second wing. Each second wing is connected to the first wing by a wing pivot assembly that includes a skewed hinge pivotably connecting one of the second wings to the first wing. The wing pivot assembly allows each second wing to pivot with respect to the first wing between an operating position and a transport position, in which the skewed hinge defines a first pivot axis oriented at an acute angle with respect to the longitudinal axis.